SoroushVahidi/scidocs huggingface dataset:
Answering Schrödinger's question: A free-energy formulation
(2018)

The free-energy principle (FEP) is a formal model of neuronal processes that is widely recognised in neuroscience as a unifying theory of the brain and biobehaviour. More recently, however, it has been extended beyond the brain to explain the dynamics of living systems, and their unique capacity to avoid decay. The aim of this review is to synthesise these advances with a meta-theoretical ontology of biological systems called variational neuroethology, which integrates the FEP with Tinbergen's four research questions to explain biological systems across spatial and temporal scales. We exemplify this framework by applying it to Homo sapiens, before translating variational neuroethology into a systematic research heuristic that supplies the biological, cognitive, and social sciences with a computationally tractable guide to discovery.
Unseen Noise Estimation Using Separable Deep Auto Encoder for Speech Enhancement
(2016)

Unseen noise estimation is a key yet challenging step to make a speech enhancement algorithm work in adverse environments. At worst, the only prior knowledge we know about the encountered noise is that it is different from the involved speech. Therefore, by subtracting the components which cannot be adequately represented by a well defined speech model, the noises can be estimated and removed. Given the good performance of deep learning in signal representation, a deep auto encoder (DAE) is employed in this work for accurately modeling the clean speech spectrum. In the subsequent stage of speech enhancement, an extra DAE is introduced to represent the residual part obtained by subtracting the estimated clean speech spectrum (by using the pre-trained DAE) from the noisy speech spectrum. By adjusting the estimated clean speech spectrum and the unknown parameters of the noise DAE, one can reach a stationary point to minimize the total reconstruction error of the noisy speech spectrum. The enhanced speech signal is thus obtained by transforming the estimated clean speech spectrum back into time domain. The above proposed technique is called separable deep auto encoder (SDAE). Given the under-determined nature of the above optimization problem, the clean speech reconstruction is confined in the convex hull spanned by a pre-trained speech dictionary. New learning algorithms are investigated to respect the non-negativity of the parameters in the SDAE. Experimental results on TIMIT with 20 noise types at various noise levels demonstrate the superiority of the proposed method over the conventional baselines.
A variable splitting augmented Lagrangian approach to linear spectral unmixing
(2009)

This paper presents a new linear hyperspectral unmixing method of the minimum volume class, termed simplex identification via split augmented Lagrangian (SISAL). Following Craig's seminal ideas, hyperspectral linear unmixing amounts to finding the minimum volume simplex containing the hyperspectral vectors. This is a nonconvex optimization problem with convex constraints. In the proposed approach, the positivity constraints, forcing the spectral vectors to belong to the convex hull of the endmember signatures, are replaced by soft constraints. The obtained problem is solved by a sequence of augmented Lagrangian optimizations. The resulting algorithm is very fast and able so solve problems far beyond the reach of the current state-of-the art algorithms. The effectiveness of SISAL is illustrated with simulated data.
Deep 3D Convolutional Encoder Networks With Shortcuts for Multiscale Feature Integration Applied to Multiple Sclerosis Lesion Segmentation
(2016)

We propose a novel segmentation approach based on deep 3D convolutional encoder networks with shortcut connections and apply it to the segmentation of multiple sclerosis (MS) lesions in magnetic resonance images. Our model is a neural network that consists of two interconnected pathways, a convolutional pathway, which learns increasingly more abstract and higher-level image features, and a deconvolutional pathway, which predicts the final segmentation at the voxel level. The joint training of the feature extraction and prediction pathways allows for the automatic learning of features at different scales that are optimized for accuracy for any given combination of image types and segmentation task. In addition, shortcut connections between the two pathways allow high- and low-level features to be integrated, which enables the segmentation of lesions across a wide range of sizes. We have evaluated our method on two publicly available data sets (MICCAI 2008 and ISBI 2015 challenges) with the results showing that our method performs comparably to the top-ranked state-of-the-art methods, even when only relatively small data sets are available for training. In addition, we have compared our method with five freely available and widely used MS lesion segmentation methods (EMS, LST-LPA, LST-LGA, Lesion-TOADS, and SLS) on a large data set from an MS clinical trial. The results show that our method consistently outperforms these other methods across a wide range of lesion sizes.
From Skimming to Reading: A Two-stage Examination Model for Web Search
(2014)

User's examination of search results is a key concept involved in all the click models. However, most studies assumed that eye fixation means examination and no further study has been carried out to better understand user's examination behavior. In this study, we design an experimental search engine to collect both the user's feedback on their examinations and the eye-tracking/click-through data. To our surprise, a large proportion (45.8%) of the results fixated by users are not recognized as being "read". Looking into the tracking data, we found that before the user actually "reads" the result, there is often a "skimming" step in which the user quickly looks at the result without reading it. We thus propose a two-stage examination model which composes of a first "from skimming to reading" stage (Stage 1) and a second "from reading to clicking" stage (Stage 2). We found that the biases (e.g. position bias, domain bias, attractiveness bias) considered in many studies impact in different ways in Stage 1 and Stage 2, which suggests that users make judgments according to different signals in different stages. We also show that the two-stage examination behaviors can be predicted with mouse movement behavior, which can be collected at large scale. Relevance estimation with the two-stage examination model also outperforms that with a single-stage examination model. This study shows that the user's examination of search results is a complex cognitive process that needs to be investigated in greater depth and this may have a significant impact on Web search.
Artificial Intelligence Technique Applied to Intrusion Detection
(2012)

Communication network is facilitated with different protocol .Each protocol supported to increase the network performance in a secured manner. In communication process, user’s connectivity, violations of policy on access of information are handles through intrusion. Intrusion prevention is the process of performing intrusion detection and attempting to stop detected possible incidents. It focused on identifying possible incidents, logging information about them, attempting to stop them, and reporting them to security administrators. However, organizations use Intrusion detection and prevention system (IDPS) for other purposes, such as identifying problems with security policies, documenting existing threats, and determining individuals from violating security policies. Communication architecture is built up on IP.Internet Control Message Protocol (ICMP ) protocol is tightly integrated with IP. ICMP messages, delivered in IP packets, are used for out-of-band messages related to network operation or mis-operation.In this paper describes about HDLC , ICMP protocol sequences which is used to detect the intrusion on hybrid network and its attributes are recommend the standardized protocol for the intrusion detection process. This standardization protocol compare the previous part of the research of HDLC and ICMP protocols.
Enhanced LSB technique for audio steganography
(2012)

The idea of this paper is to invent a new strategy in Steganography to get the minimum effect in audio which is used to hide data into it. “Progress always involves risk” Fredrick Wilcox observed that technological progress of computer science and the Internet altered the way we lived, and will continue to cast our life[1] . In this paper we have presented a Steganography method of embedding text data in an audio file. The basic approach behind this paper is to provide a good, well-organized method for hiding the data and sent to the destination in safer manner. In the proposed technique first the audio file is sampled and then appropriate bit is modified. In selected sample one bit is modified at least significant bit .The remaining bits may be used but it may be cause noise. We have attempted to provide an overview, theoretical framework about audio Steganography techniques and a novel approach to hide data in an audio using least significant bit (LSB).
A stable-isotope dilution GC-MS approach for the analysis of DFRC (derivatization followed by reductive cleavage) monomers from low-lignin plant materials.
(2015)

The derivatization followed by reductive cleavage (DFRC) method is a well-established tool to characterize the lignin composition of plant materials. However, the application of the original procedure, especially the chromatographic determination of the DFRC monomers, is problematic for low-lignin foods. To overcome these problems a modified sample cleanup and a stable-isotope dilution approach were developed and validated. To quantitate the diacetylated DFRC monomers, their corresponding hexadeuterated analogs were synthesized and used as internal standards. By using the selected-ion monitoring mode, matrix-associated interferences can be minimized resulting in higher selectivity and sensitivity. The modified method was applied to four low-lignin samples. Lignin from carrot fibers was classified as guaiacyl-rich whereas the lignins from radish, pear, and asparagus fibers where classified as balanced lignins (guaiacyl/syringyl ratio=1-2).
Action Design Research and Visualization Design
(2016)

In applied visualization research, artifacts are shaped by a series of small design decisions, many of which are evaluated quickly and informally via methods that often go unreported and unverified. Such design decisions are influenced not only by visualization theory, but also by the people and context of the research. While existing applied visualization models support a level of reliability throughout the design process, they fail to explicitly account for the influence of the research context in shaping the resulting design artifacts. In this work, we look to action design research (ADR) for insight into addressing this issue. In particular, ADR offers a framework along with a set of guiding principles for navigating and capitalizing on the disruptive, subjective, human-centered nature of applied design work, while aiming to ensure reliability of the process and design, and emphasizing opportunities for conducting research. We explore the utility of ADR in increasing the reliability of applied visualization design research by: describing ADR in the language and constructs developed within the visualization community; comparing ADR to existing visualization methodologies; and analyzing a recent design study retrospectively through the lens of ADR's framework and principles.
An X-band to Ka-band SPDT switch using 200 nm SiGe HBTs
(2012)

This paper presents the design and measured performance of an X-band to Ka-band SiGe HBT SPDT switch. The proposed SPDT switch was fabricated using a 200 nm, 150 GHz peak fT silicon-germanium (SiGe) heterojunction bipolar transistor (HBT) BiCMOS technology. The SPDT switch design uses diode-connected SiGe HBTs in a series-shunt configuration to improve the switch bandwidth and isolation. Between 8 and 40 GHz, this SPDT switch achieves an insertion loss of less than 4.3 dB, an isolation of more than 20.3 dB, and a return loss of more than 9 dB.
Measuring dimensions of intergenerational contact: factor analysis of the Queen's University Scale.
(2018)

OBJECTIVES
Intergenerational contact has been linked to a range of health outcomes, including greater engagement and lower depression. Measures of contact are limited. Informed by Allport's contact theory, the Queen's University Scale consists of items rating contact with elders. We administered the survey to a young adult sample (N = 606) to identify factors that may optimize intervention programming and enhance young persons' health as they age.


METHODS
We conducted exploratory factor analysis (EFA) in the structural equation modeling framework and then confirmatory factor analysis with items pertaining to the general elder population.


RESULTS
EFAs did not yield an adequate factor structure. We tested two alternative confirmatory models based on findings from the EFA. Neither a second-order model nor a first-order model allowing double loadings and correlated errors proved adequate.


CONCLUSION
Difficulty finding an adequate factor solution reflects challenges to measuring intergenerational contact with this scale. Items reflect relevant topics but subscale models are limited in interpretability. Knox and colleagues' analyses led them to recommend a brief, global scale, but we did not find empirical support for such a measure. Next steps include development and testing of a reliable, valid scale measuring dimensions of contact as perceived by both youth and elders.
End of Moore ’ s law : thermal ( noise ) death of integration in micro and nano electronics
(2002)

The exponential growth of memory size and clock frequency in computers has a great impact on everyday life. The growth is empirically described by Moore’s law of miniaturization. Physical limitations of this growth would have a serious impact on technology and economy. A thermodynamical effect, the increasing thermal noise voltage (Johnson–Nyquist noise) on decreasing characteristic capacitances, together with the constrain of using lower supply voltages to keep power dissipation manageable on the contrary of increasing clock frequency, has the potential to break abruptly Moore’s law within 6–8 years, or earlier.  2002 Elsevier Science B.V. All rights reserved.
Low-power 4-2 and 5-2 compressors
(2001)

This paper explores various low power higher order compressors such as 4-2 and 5-2 compressor units. These compressors are building blocks for binary multipliers. Various circuit architectures for 4-2 compressors are compared with respect to their delay and power consumption. The different circuits are simulated using HSPICE. A new circuit for a 5-2 compressor is then presented which is 12% faster and consumes 37% less power.
Analysis of jitter due to power-supply noise in phase-locked loops
(2000)

Phase-locked loops (PLL) in RF and mixed signal VLSI circuits experience supply noise which translates to a timing jitter. In this paper an analysis of the timing jitter due to the noise on the power supply rails is presented. Stochastic models of the power supply noise in VLSI circuits for different values of on-chip decoupling capacitances are presented first. This is followed by calculation of the phase noise of the voltage-controlled oscillator (VCO) in terms of the statistical properties of supply noise. Finally the timing jitter of PLL is predicted in response to the VCO phase noise. A PLL circuit has been designed in 0.35μ CMOS process, and our mathematical model was applied to determine the timing jitter. Experimental results prove the accuracy of the predicted model.
Performance analysis of low-power 1-bit CMOS full adder cells
(2002)

A performance analysis of 1-bit full-adder cell is presented. The adder cell is anatomized into smaller modules. The modules are studied and evaluated extensively. Several designs of each of them are developed, prototyped, simulated and analyzed. Twenty different 1-bit full-adder cells are constructed (most of them are novel circuits) by connecting combinations of different designs of these modules. Each of these cells exhibits different power consumption, speed, area, and driving capability figures. Two realistic circuit structures that include adder cells are used for simulation. A library of full-adder cells is developed and presented to the circuit designers to pick the full-adder cell that satisfies their specific applications.
Harvesting Big Data to Enhance Supply Chain Innovation Capabilities : An Analytic Infrastructure Based on Deduction Graph
(2016)

Today, firms can access to big data (tweets, videos, click streams, and other unstructured sources) to extract new ideas or understanding about their products, customers, and markets. Thus, managers increasingly view data as an important driver of innovation and a significant source of value creation and competitive advantage. To get the most out of the big data (in combination with a firm’s existing data), a more sophisticated way of handling, managing, analysing and interpreting data is necessary. However, there is a lack of data analytics techniques to assist firms to capture the potential of innovation afforded by data and to gain competitive advantage. This research aims to address this gap by developing and testing an analytic infrastructure based on the deduction graph technique. The proposed approach provides an analytic infrastructure for firms to incorporate their own competence sets with other firms. Case studies results indicate that the proposed data analytic approach enable firms to utilise big data to gain competitive advantage by enhancing their supply chain innovation capabilities.
Capturing the mood: facebook and face-to-face encounters in the workplace
(2014)

What makes people feel happy, engaged and challenged at work? We conducted an in situ study of Facebook and face-to-face interactions examining how they influence people's mood in the workplace. Thirty-two participants in an organization were each observed for five days in their natural work environment using automated data capture and experience sampling. Our results show that online and offline social interactions are associated with different moods, suggesting that they serve different purposes at work. Face-to-face interactions are associated with a positive mood throughout the day whereas Facebook use and engagement in work contribute to a positive feeling at the end of the day. Email use is associated with negative affect and along with multitasking, is associated with a feeling of engagement and challenge throughout the day. Our findings provide initial evidence of how online and offline interactions affect workplace mood, and could inform practices to improve employee morale.
A Survey of Non-conventional Techniques for Low-voltage Low-power Analog Circuit Design
(2013)

Designing integrated circuits able to work under low-voltage (LV) low-power (LP) condition is currently undergoing a very considerable boom. Reducing voltage supply and power consumption of integrated circuits is crucial factor since in general it ensures the device reliability, prevents overheating of the circuits and in particular prolongs the operation period for battery powered devices. Recently, non-conventional techniques i.e. bulkdriven (BD), floating-gate (FG) and quasi-floating-gate (QFG) techniques have been proposed as powerful ways to reduce the design complexity and push the voltage supply towards threshold voltage of the MOS transistors (MOST). Therefore, this paper presents the operation principle, the advantages and disadvantages of each of these techniques, enabling circuit designers to choose the proper design technique based on application requirements. As an example of application three operational transconductance amplifiers (OTA) based on these non-conventional techniques are presented, the voltage supply is only ±0.4 V and the power consumption is 23.5 μW. PSpice simulation results using the 0.18 μm CMOS technology from TSMC are included to verify the design functionality and correspondence with theory.
Listening to music and physiological and psychological functioning: the mediating role of emotion regulation and stress reactivity.
(2012)

Music listening has been suggested to have short-term beneficial effects. The aim of this study was to investigate the association and potential mediating mechanisms between various aspects of habitual music-listening behaviour and physiological and psychological functioning. An internet-based survey was conducted in university students, measuring habitual music-listening behaviour, emotion regulation, stress reactivity, as well as physiological and psychological functioning. A total of 1230 individuals (mean = 24.89 ± 5.34 years, 55.3% women) completed the questionnaire. Quantitative aspects of habitual music-listening behaviour, i.e. average duration of music listening and subjective relevance of music, were not associated with physiological and psychological functioning. In contrast, qualitative aspects, i.e. reasons for listening (especially 'reducing loneliness and aggression', and 'arousing or intensifying specific emotions') were significantly related to physiological and psychological functioning (all p = 0.001). These direct effects were mediated by distress-augmenting emotion regulation and individual stress reactivity. The habitual music-listening behaviour appears to be a multifaceted behaviour that is further influenced by dispositions that are usually not related to music listening. Consequently, habitual music-listening behaviour is not obviously linked to physiological and psychological functioning.
Product type and consumers' perception of online consumer reviews
(2011)

Consumers hesitate to buy experience products online because it is hard to get enough information about experience products via the Internet. Online consumer reviews may change that, as they offer consumers indirect experiences about dominant attributes of experience products, transforming them into search products. When consumers are exposed to an online consumer review, it should be noted that there are different kinds of review sources. This study investigates the effects of review source and product type on consumers’ perception of a review. The result of the online experiment suggests that product type canmoderate consumers’ perceived credibility of a review from different review sources, and the major findings are: (1) consumers are more influenced by a review for an experience product than for a search product when the review comes from consumer-developed review sites, and (2) a review from an online community is perceived to be the most credible for consumers seeking information about an experience product. The findings provide managerial implications for marketers as to how they can better manage online consumer reviews.